1. Field of the Invention
The present invention relates to a pulse wave detecting device for detecting pulse waves, and to a pulse measurer employing the aforementioned pulse wave detecting device.
2. Description of the Related Art
Pulse measurers which detect pulse waves, calculate the pulse rate, and then notify the user of the calculated result have been commercially available for some time. This type of pulse measurer calculates the pulse rate using the signals (pulse wave signals) output from a pulse wave detecting sensor that is disposed near a site on the user's body where the pulse measurement is to be made. Known methods for calculating the pulse rate include the rectangular wave processing method and frequency analysis method described below.
(A) Rectangular wave processing method
In the rectangular wave processing method, the pulse wave signal is converted to a rectangular wave, and the pulse rate is calculated by measuring the period of the rectangular wave (the pulse rate is proportional to the reciprocal of the period). In other words, the pulse rate can be calculated by investigating the variation in the level of the pulse wave signal over a time domain. Thus, this method enables calculation of the pulse rate by only a small amount of calculations and a small-scale circuit structure.
(B) Frequency analysis method
In the frequency analysis method, the pulse wave signal is subjected to frequency analysis, the spectral line having a maximal level is extracted from the spectrum obtained as a result of the frequency analysis, and the pulse rate is calculated from the frequency of this spectral line. In other words, the pulse rate is calculated by comparing the levels of the pulse wave signals within a frequency domain. FFT is typically employed as the frequency analysis method.
However, in addition to the pulse wave components, other noise may be superimposed on the output from the pulse wave detecting sensor. Since this superimposed noise is not necessarily regular, merely providing an analog filter at the input stage does not sufficiently remove its effects. Accordingly, the present inventors have proposed the following processes (1) through (3) for reducing such noise.
(1) Impulse noise removal processing
As used here, impulse noise is the general term for noise which is generated suddenly. An example of a pulse wave signal containing superimposed impulse noise is shown in FIG. 11. FIG. 11(a) shows the pulse wave signal in the time domain, while FIG. 11(b) shows the spectrum obtained after performing an FFT on this pulse wave signal. As is clear from the figures, due to the superimposition of impulse noise, the pulse wave signal is extremely deformed over the time period t1.about.t2 in FIG. 11(a), and a spectral line is present which is higher than spectral line SP which shows the fundamental wave of the pulse wave. As described above, in the frequency analysis method, the pulse rate is calculated based on the highest level spectral line. Thus, since frequency analysis is performed on the pulse wave signal containing the superimposed impulse noise as shown in the figure, it is not possible to accurately calculate the pulse rate.
Therefore, the present inventors proposed a device which monitors for the presence or absence of phenomena which cause impulse noise to be generated, and when, based on the results of this monitoring, there is a concern that impulse noise may be superimposed, performs frequency analysis after inserting a dummy signal in the interval containing the impulse noise in the pulse signal (for example, time period t1.about.t2 in FIG. 11(a)) (for details, see specification and figures accompanying Japanese Patent Application No. 273238 of 1995: Japanese Patent First Publication No. 113653 of 1997). In this device, because a dummy signal having a value of 0 is inserted in the time interval t1.about.t2 in which the impulse noise is superimposed, spectral line SP, which expresses the fundamental wave of the pulse wave, becomes the highest level spectral line in the spectrum obtained as a result of FFT processing. Note that, as is clear from FIGS. 12(a) and 12(b), the above-described device is premised on the use of frequency analysis.
(2) Window processing
Typically, the change in the pulse wave (pulse rate) is continuous, with there being only a slight chance of a large deviation from the previously detected value. Window processing is processing which takes advantage of this fact to set a suitable range (window) for the current detection value by multiplying the value detected previously by a fixed coefficient and, when a detected value outside the range is obtained, which removes this value as an anomalous value resulting from noise. When there is poor following of the pulse rate by the window, then, if the pulse rate changes abruptly such as at the start of exercise (t1) or the like, the pulse rate cannot be followed, as shown in FIG. 13. As a result, a phenomenon occurs in which even if the detected value is a normal value, it is removed as an anomalous value. Moreover, this phenomenon continues until the window is correctly revised. The present inventors have therefore proposed a technique for improving the window's ability to follow the pulse rate (for details, see specification and figures accompanying Japanese Patent Application No. 24511 of 1996: Japanese Patent Application First Publication No. 154825 of 1997).
(3) Processing to remove body motion component
As explained above, the pulse wave detection sensor is typically disposed near the site on the user's body where measurements are to be made. Accordingly, when the user is exercising, a body motion component is superimposed on the pulse wave signal. An example of the spectrum obtained from performing FFT on a pulse wave signal containing a superimposed body motion component is shown in FIG. 14(a). In the example shown in this figure, the spectral lines on the left are the pulse wave components, while the spectral lines on the right are the body motion components. The spectral lines of both these groups are of approximately the same level. Of course, FIG. 14(a) is merely one example, and a situation is also possible in which the highest level spectral line is present among the spectral lines for the body motion component. Accordingly, if frequency analysis is carried out on a pulse wave signal containing a superimposed body motion component, the correct pulse rate cannot be calculated.
Therefore, the present inventors proposed a device comprising a body motion detecting sensor which subtracts the spectrum (14(b)) obtained by performing FFT on the signal (i.e., the body motion signal) output from the body motion detecting sensor from the spectrum shown in FIG. 14(a), and then selects the highest level spectral line after obtaining a spectrum that consists of only pulse wave components such shown in FIG. 14(c) (for details, see Japanese Patent Application No. 227338 of 1995). As is clear from this figure, by means of this device, the selected spectral line is spectral line SP which expresses the fundamental wave of the pulse wave. The device described here is premised on the use of frequency analysis, as should be clear from the fact that spectrum subtraction is carried out.
In the impulse noise removal processing described under (1) above, phenomenon causing impulse noise, for example, features employed in a wristwatch like a flashing back light or a sounding alarm, are set in advance, and a dummy signal is inserted in the pulse wave signal at the time which has been set for the occurrence of these phenomenon. However, general impulse noise may also occur which is not related to the internal state of the device itself, making it extremely difficult to detect all these phenomena. On the other hand, if the device is designed so that a dummy signal is inserted regardless of the generation of such phenomenon, then it is possible to completely remove the impulse noise. However, the essential pulse wave components are also removed entirely. In other words, removal of all the impulse noise while having only a minimal effect on the essential pulse wave components is extremely difficult to accomplish by means of the only the processing described in (1) above.
Moreover, in the case of the window processing described under (2) above, values detected outside the window are removed, so that when changes in the window cannot follow changes in the pulse wave (when an arrhythmia has occurred for example), an accurately detected value is removed as an anomalous value.
Finally, in the body motion component removal processing described under (3) above, spectrum subtraction is carried out. However, because the body motion components (on the left in FIG. 14(a)) in the output from the pulse wave detecting sensor, and the body motion components (FIG. 14(b)) in the output from the body motion detecting sensor do not in fact completely coincide, it is not possible to completely remove the body motion component by subtracting the latter from the former.